Adaptive Cornea Modeling from Keratometric Data
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Purpose: To introduce an iterative, multiscale procedure that allows for better reconstruction of the shape of the anterior surface of the cornea from altimetric data collected by a corneal topographer. Methods: The report describes, first, an adaptive, multiscale mathematical algorithm for the parsimonious fit of the corneal surface data that adapts the number of functions used in the reconstruction to the conditions of each cornea. The method also implements a dynamic selection of the parameters and the management of noise. Then, several numerical experiments are performed, comparing it with the results obtained by the standard Zernike-based procedure. Results: The numerical experiments showed that the algorithm exhibits steady exponential error decay, independent of the level of aberration of the cornea. The complexity of each anisotropic Gaussian-basis function in the functional representation is the same, but the parameters vary to fit the current scale. This scale is determ...